利用虛擬實境駕駛模擬進行動態刺激下之腦波反應研究

Abstract

本論文以腦電波(Electroencephalogram, EEG)研究駕車動態刺激下之人類認知反應，為研究特定行車事件下之人類認知狀態，研究中使用基於虛擬實境技術之動態駕車模擬裝置來建立一逼真之駕車環境及駕車事件，包括在公路上的車輛加速、減速及偏移。駕車模擬裝置中使用液壓六軸動態平臺提供駕駛員的動態感覺，此平臺依照車輛不同方向的加速度變化會做出相對的傾斜動作。為了找出動態刺激對認知狀態之影響，我們比較平臺開啟/關閉兩種狀態下受測者的EEG訊號來研究動態刺激對認知狀態的影響。 首先，EEG訊號經過獨立成份分析(Independent Component Analysis, ICA)後分離成數個獨立的訊號源。結果顯示出在運動皮質區有獨立之成份，並且與加減速行車動態相關之 Alpha 頻帶 (8~12Hz) 能量抑制，並且在不同次實驗之間有很高的一致性。而在動態偏移事件中，我們發現在大腦中心線 (Central Midline) 位置有負電位的產生。所發現的大腦動態結果在不同受測者之間表現出重複的特性。本論文以事件相關電位(Event Related Potential)及事件相關頻譜擾動(Event Related Spectral Perturbation)觀察腦動態，並首次發現可辨認、不同類動態刺激相關之腦電波。實驗結果幫助我們更了解與動態感知相關的腦神經網路，也奠定了動態刺激與腦電波之相關性研究一個重要基礎。

The purpose of this study is to investigate Electroencephalography (EEG) dynamics in response to kinesthetic stimuli during driving. To study human cognition under specific driving task, we used Virtual Reality (VR) based driving simulator to create practical driving events; including acceleration, deceleration and deviation. The driving simulator includes Hydraulic Hexapod Motion Platform that provides tilt mechanism (to give roll, yaw, etc.) to simulate vehicle movement. In this study, we compare the EEG dynamics in response to kinesthetic stimulus while the platform is in action, compared to that were recorded when the platform is stationary. The scalp-recorded EEG channel signals were first separated into independent brain sources by Independent Component Analysis (ICA), then analyzed in time and frequency domains. Our results showed that independent component processes near the somatomotor cortex exhibited alpha power decreases that were consistent across sessions within subjects. Negative potential phase-locked to deviation events under motion condition was observed in a midline central component, which was consisted with the finding in the literature. The brain dynamics appears reproducible across sessions and subjects. This thesis, for the first time in the literature, reports distinctive brain dynamics measured by Event-Related-Potentials (ERP) and Event-Related-Spectral-Perturbations (ERSP) in response to kinesthetic inputs of different types. The results help us to better understand different brain networks involving in driving and provide a foundation in studying EEG activities related to kinesthetic stimuli.